The digital paradigm is exerting a profound impact on biomedicine. Examples are provided in many contexts and due to a few main factors:
a) increasing centralization of Electronic Health Records (EHR) in public health and epidemiological studies and their presence in scientific publications;
b) foundational role of high-throughput genomics in the discovery pipeline;
c) emphasis on integrated multiplexed omics to advance experimental biology;
d) diffusion of high-resolution imaging now achieving unprecedented accuracy in precision diagnostics and therapy assessment.
In light of the ongoing switch of medicine paradigm, the role of digital phenotypes has become crucial to characterize diseases. Comprehensive approaches are now conceived for the analysis of multi-evidenced data, i.e. data generated from multiple sources.
The emerging N-of-1 paradigm, which is inspired by individualization of care and cure, is destined to
drive important changes in targeted treatments and drug re-purposing.
The main questions that need to be addressed by the studies and applications welcomed in this Research Topic are:
1. Can digitalization already be considered disruptive in medicine?
2. Are EHRs filling the knowledge of clinical gaps in support of patients?
3. Is Big Data helping doctors stop Big Killers?
The digital paradigm is exerting a profound impact on biomedicine. Examples are provided in many contexts and due to a few main factors:
a) increasing centralization of Electronic Health Records (EHR) in public health and epidemiological studies and their presence in scientific publications;
b) foundational role of high-throughput genomics in the discovery pipeline;
c) emphasis on integrated multiplexed omics to advance experimental biology;
d) diffusion of high-resolution imaging now achieving unprecedented accuracy in precision diagnostics and therapy assessment.
In light of the ongoing switch of medicine paradigm, the role of digital phenotypes has become crucial to characterize diseases. Comprehensive approaches are now conceived for the analysis of multi-evidenced data, i.e. data generated from multiple sources.
The emerging N-of-1 paradigm, which is inspired by individualization of care and cure, is destined to
drive important changes in targeted treatments and drug re-purposing.
The main questions that need to be addressed by the studies and applications welcomed in this Research Topic are:
1. Can digitalization already be considered disruptive in medicine?
2. Are EHRs filling the knowledge of clinical gaps in support of patients?
3. Is Big Data helping doctors stop Big Killers?
